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Category: genetics

Ancestry-Associated Performance Variability of Open-Source AI Models for EGFR Prediction in Lung Cancer

Open-source AI models for LungCancer EGFR mutation prediction showed high accuracy overall but reduced performance in Asian patients and pleural samples, indicating the need for broader validation.

Importance Artificial intelligence (AI) models are emerging as rapid, low-cost tools for predicting targetable genomic alterations directly from routine pathology slides. Although these approaches could accelerate treatment decisions in lung cancer, little is known about whether their performance is consistent across diverse patient populations and tissue contexts.

Objective To evaluate the performance and generalizability of 2 open-source AI pathology models for predicting EGFR mutation status in lung adenocarcinoma (LUAD) across independent cohorts and ancestral subgroups.

Design, Setting, and Participants This cohort study included patients with LUAD from 2 cohorts: Dana-Farber Cancer Institute (DFCI) from June 2013 to November 2023, and a European-based trial (TNM-I) from August 2016 to February 2022. All patients had paired next-generation sequencing data and hematoxylin-eosin–stained whole-slide images. In the DFCI cohort, genetic ancestry was inferred using germline genotype data. Data analyses were performed from July 2025 to September 2025.

Studies show 11 genetic variants affect gut microbiome

In two new studies on 28,000 individuals, researchers are able to show that genetic variants in 11 regions of the human genome have a clear influence on which bacteria are in the gut and what they do there. Only two genetic regions were previously known. Some of the new genetic variants can be linked to an increased risk of gluten intolerance, hemorrhoids and cardiovascular diseases.

The studies are published in the journal Nature Genetics.

The community of bacteria living in our gut, or gut microbiome, has become a hot research area in recent years because of its great significance for health and disease. However, the extent to which our genes determine which bacteria are present in the intestines has been unclear. Until now, it has only been possible to link a few genetic variants to the composition of the gut microbiome with certainty.

Discussing the implication of DNA methylation in human diseases

DNA methylation plays a critical role in gene expression regulation and has emerged as a robust biomarker of biological age. This modification will become heavier or site drift along with aging. Recently, it is termed epigenetic clocks—such as Horvath, Hannum, PhenoAge, and GrimAge—leverage specific methylation patterns to accurately predict age-related decline, disease risk, and mortality. These tools are now widely applied across diverse tissues, populations, and disease contexts. Beyond age-related loss of methylation control, accelerated DNA methylation age has been linked to environmental exposures, lifestyle factors, and chronic diseases, further reinforcing its value as a dynamic and clinically relevant marker of biological aging. DNA methylation is reshaping our understanding of aging and disease risk, with promising implications for preventive medicine and interventions aimed at promoting healthy longevity. However, it must be admitted that some challenges remain, including limited generalizability across populations, an unclear mechanism, and inconsistent longitudinal performance. In this review, we examine the biological foundations of DNA methylation, major advances in epigenetic clock development, and their expanding applications in aging research, disease prediction and health monitoring.

Aging is a complex, multifactorial process that affects nearly all biological systems. While chronological age simply measures the passage of time from birth, biological age reflects the functional state and health of an individual’s tissues and organs (Kiselev et al., 2025). This distinction is critical, as individuals of the same chronological age often exhibit markedly different biological conditions, disease risks, and mortality trajectories (Dugue et al., 2018). Therefore, biological age potentially serves as a more meaningful measure of aging-related decline and is increasingly used to assess overall health status, predict disease onset, and evaluate the effectiveness of interventions aimed at promoting healthy longevity (Dugue et al., 2018; Petkovich et al., 2017).

Among various biomarkers proposed to estimate biological age, epigenetic modifications—particularly DNA methylation—have emerged as one of the most reliable and informative (Dugue et al., 2018). In epigenetics, DNA methylation involves the addition of a methyl group to the 5′ position of cytosine residues, typically at CpG dinucleotides, which can regulate gene expression without altering the underlying DNA sequence. Moreover, DNA methylation can be accurately measured by sequencing at methylated sites with bisulfate treatment (Zhang et al., 2012). Age-related changes in DNA methylation pattern are not random; they occur at specific genomic locations. These methylated sites are picked and constitute come patterns, by which scientists can construct “epigenetic clocks” to precisely estimate a person’s biological age based on their DNA modification. As people grow older, their methylation profiles shift in predictable ways (Kiselev et al., 2025; Horvath, 2013; Horvath and Raj, 2018).

A Deep Dive Into The ‘Longevity Vitamin’, Ergothionine

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Blood-based tests show strong promise for dementia diagnosis—but population diversity matters

In a study published today, Friday, February 13, 2026, in the journal Nature Aging, researchers show that blood-based biomarkers can support accurate dementia diagnosis across diverse populations when integrated with cognitive and neuroimaging measures. Blood-based biomarkers are emerging as one of the most promising advances for the global diagnosis of dementia, including Alzheimer’s disease and frontotemporal lobar degeneration. These tests offer a more accessible, scalable, and cost-effective alternative to traditional diagnostic tools such as brain imaging or cerebrospinal fluid analysis.

However, most blood-based biomarkers have been developed and validated primarily in relatively homogeneous populations. Genetic background, overall physical health, and environmental and social exposures can substantially influence biomarker levels, raising concerns about how well these tests perform across diverse populations worldwide.

Convergent molecular pathways across distinct genetic forms of autism

The new study, published in the journal Nature, provides new insights by demonstrating that while different mutations affect the developing brain in initially distinct ways, they increasingly impact overlapping molecular pathways as development progresses.

Researchers monitored the gene expression of the organoids over 100 days as they developed, which allowed researchers to observe how genetic changes affect brain during the critical early development windows.

Early in development, each genetic form showed distinct molecular signatures. However, as the organoids matured, these different mutations increasingly affected similar biological processes, particularly those involved in neuronal maturation and synapse formation.

The researchers identified a network of genes involved in regulating gene expression and chromatin remodeling, which is the process by which DNA is packaged and made accessible for reading. This network appears to play a central role in this convergence. Using CRISPR technology to individually reduce the activity of these regulatory genes in neural cells, the team confirmed that many of them control downstream pathways were previously linked to autism.

Notably, the study found few consistent molecular changes in organoids derived from individuals with idiopathic autism, likely reflecting the highly complex genetic architecture of autism that doesn’t involve major mutations. This finding underscores the need for much larger studies to understand the more common, polygenic forms of autism. ScienceMission sciencenewshighlights.

The researchers have created a comprehensive map showing how eight different genetic mutations associated with autism spectrum disorder affect early brain development, providing new insights into the ways diverse genetic causes may lead to shared features and symptoms of the disorder.

Continue reading “Convergent molecular pathways across distinct genetic forms of autism” | >

False alarm in newborn screening: How zebrafish can prevent unnecessary spinal muscular atrophy therapies

A positive newborn screening for spinal muscular atrophy (SMA) is currently considered a medical emergency. Without early treatment, severe disability or death in infancy are likely. However, research findings from Germany and Australia now show that in rare cases, a positive screening result can be a genetic false alarm. Researchers have discovered that functional tests in a zebrafish model may enable fast and reliable clinical decision-making in cases of unclear genetic findings.

The study “SMN1 variants identified by false positive SMA newborn screening tests: Therapeutic hurdles, and functional and epidemiological solutions” was published in the American Journal of Human Genetics and another study, “Clinical relevance of zebrafish for gene variants testing. Proof-of-principle with SMN1/SMA,” in EMBO Molecular Medicine. The collaborative research team was led by Professor Dr. Brunhilde Wirth, Director of the University of Cologne’s Institute of Human Genetics and Principal Investigator at the Center for Molecular Medicine Cologne (CMMC) and Dr. Jean Giacomotto from Griffith University’s Institute for Biomedicine and Glycomics, Brisbane, Australia.

The scientists examined two newborns—a girl from Germany and a boy from Australia—in whom routine screening initially failed to detect the SMN1 gene. A missing SMN1 gene is the main genetic trigger of SMA. This diagnosis would normally result in immediate treatment, as it would be assumed that the child’s life is in danger. However, further genetic analysis revealed a surprising finding: both children carried rare SMN1 variants that had not been detected by the screening test. It remains unclear whether these variants cause the disease.

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